1. Field of the Invention
The present invention relates to a system and method for detecting an epileptic seizure in a prone epileptic person.
Epileptic seizures are caused by dysfunctions of the brain which may be manifested in various ways. This disorder affects between 0.5% and 1% of the population. 70% of these patients can control their epileptic seizures by using antiepileptic medication. For the other 30% of patients, surgery may be envisaged to remove the epileptic region, in other words the parts of the brain that trigger these seizures, in order to ensure that the patient has no more seizures.
Many of the symptoms of an epileptic seizure are motor symptoms. These symptoms can be recorded and analyzed using various devices such as video or motion sensors, in order to determine the nature of a patient's seizure or detect a seizure for reasons of safety.
2. Description of the Related Art
There are known video processing methods for quantifying the motor activity of a patient during a seizure. For this purpose, markers are placed on the patient. The main advantage of this type of method is that cameras are already in use in most hospital rooms. The problems associated with these methods are due to the fact that it is difficult to analyze movement automatically from a two-dimensional image, and uncertainties can arise if the marker disappears from the field of view. Furthermore, these types of method can only be used in a room where a camera is available.
Another approach to the motor characterization of epileptic seizures is the use of inertial/magnetic sensors. These sensors have made it possible to extract relevant data concerning human movements by the processing of multidimensional signals. Many applications have thus been developed using these low-cost, non-invasive sensors. The best-known of these is undoubtedly the analysis of posture and walk, as described for example in “A magnetometer-based approach for studying human movements”, by S. Bonnet and R. Heliot, IEEE Transactions on Biomedical Engineering, vol. 54, no. 7, 2007, which proposes a 3D magnetometer-based process for the real-time evaluation of an inclination of the body to detect movements such as a change of position from seated to standing. The characterization of movements caused by neurological factors has also been investigated: for example, accelerometers have been used for Parkinson's disease and the detection of hand tremors, as described, respectively, in “The measuring set and signal processing method for the characterization of human hand tremor,” by A. Chwaleba, J. Jakubowski and K. Kwiatos, CADSM, 2003, and “Triaxial accelerometry: a method for quantifying tremor and ataxia,” by J. D. Frost, IEEE Transactions on Biomedical Engineering, vol. 25, no. 49, 1978.In relation to epilepsy, the documents, “The potential value of 3d accelerometry for detection of motor seizures in severe epilepsy,” by T. Nijsen et al., Epilepsy and Behavior, vol. 7, 2005, and “Detection of subtle nocturnal motor activity from 3d accelerometry recordings in epilepsy patients,” by T. Nijsen et al., IEEE Transactions on Biomedical Engineering, vol. 54, 2007, focus on the distinction between nocturnal movements and seizure movements. Thus sensors are attached to a patient to detect a period in which motor activity occurs. One of the assumptions of this system is that the person does not read or visit the bathroom while the system is active.
These systems are used to detect long periods of motor activity, and can therefore only operate in strictly controlled conditions; in the conditions of everyday life, their capacity to detect an epileptic seizure is very limited.